发表机构
The Jikei University School of Medicine（东京慈惠会医科大学）
机构由 AI 辅助整理，请以论文原文为准。AI 中文总结
提出病灶门控混合合成方法，利用病灶概率图协调肿瘤回归与背景合成通路，实现多指标均衡的虚拟增强乳腺MRI，在MAMA-SYNTH挑战赛排名第六。
AI 中文摘要
目的：增强乳腺MRI依赖于静脉注射钆基对比剂，这促使研究者探索仅从平扫图像合成增强后表现的方法。MAMA-SYNTH挑战赛（MICCAI 2026 Deep-Breath研讨会）通过四个指标组评估此类合成方法：图像保真度、肿瘤感兴趣区域、下游分类和下游分割。四个组的排名取平均，因此优化单一目标是不够的。材料与方法：我们开发了一种病灶门控混合合成流程。由仅使用平扫切片的平扫分割网络集成估计的病灶概率图，在空间上协调肿瘤聚焦回归通路和背景聚焦Pix2PixHD合成通路，随后对预测增强进行区域依赖校准。训练使用公开的MAMA-MIA数据集，并按患者级别划分。推理仅需单个平扫2D切片，无需掩膜、无需增强后图像、无需除图像几何之外的辅助元数据。结果：在内部验证（n=120例患者）中，该方法达到MSE 0.523、LPIPS 0.185、肿瘤区域SSIM 0.495。该方法以自包含推理容器形式提交至隐藏的外部300例测试队列。该方法在官方MAMA-SYNTH挑战赛排行榜中排名第六。结论：从平扫图像导出的测试兼容病灶概率图能够协调互补的肿瘤聚焦回归和背景聚焦感知合成，从而在多指标挑战设置下实现平衡的虚拟增强。
英文摘要
Purpose: Contrast-enhanced breast MRI depends on intravenous gadolinium-based contrast agents, motivating methods that synthesise post-contrast appearance from pre-contrast images alone. The MAMA-SYNTH Challenge (MICCAI 2026 Deep-Breath Workshop) evaluates such synthesis across four metric groups: image fidelity, tumour region of interest, downstream classification, and downstream segmentation. The four group ranks are averaged, so optimising a single objective is insufficient. Materials and Methods: We developed a lesion-gated hybrid synthesis pipeline. A lesion probability map, estimated from the pre-contrast slice alone by an ensemble of pre-contrast-only segmentation networks, spatially coordinates a tumour-focused regression pathway and a background-focused Pix2PixHD synthesis pathway, followed by a region-dependent calibration of the predicted enhancement. Training used the public MAMA-MIA collection with a patient-level split. Inference consumes a single pre-contrast 2D slice, with no mask, no post-contrast image, and no auxiliary metadata beyond image geometry. Results: On internal validation (n = 120 patients) the method reached MSE 0.523, LPIPS 0.185, and tumour-region SSIM 0.495. It was submitted to the hidden external 300-case test cohort as a self-contained inference container. The method ranked sixth in the official MAMA-SYNTH Challenge leaderboard. Conclusion: A test-compatible lesion probability map derived from the pre-contrast image can coordinate complementary tumour-focused regression and background-focused perceptual synthesis, enabling balanced virtual contrast enhancement under a multi-metric challenge setting.
Comments8 pages, 2 figures, 3 tables. MAMA-SYNTH Challenge solution report; the submitted method ranked 6th in the official challenge leaderboard
